Application of SBM-DEA model in comprehensive quantitative evaluation of reservoir
-
摘要: 针对传统储层评价方法中人为主观性较强、计算过程复杂、结果分析不充分等问题,根据数据包络分析原理,探讨SBM-DEA模型在储层综合定量评价中的应用。实践表明,该模型在储层评价中具有以下优点:①能同时考虑多个正相关和负相关指标,无需事先给定评价标准及指标权重值,避免主观因素影响,具有较强客观性;②以线性规划为工具,无需进行指标无量纲化等数据预处理,有效简化评价过程;③评价结果介于0~1之间,除对评价单元进行排序、分类外,还可以提供评价非有效的原因及可改进信息。将其应用到苏里格气田苏X井区盒8下亚段低渗透气藏早期储层分类评价和刻画中,将研究区储层分为4类,其中Ⅰ,Ⅱ类为有利储层,总体评价结果与传统模糊综合评价结果具有较好对应关系,与气田生产实际及地质认识也基本吻合,并给出了评价实例非有效的主要差距及改进措施,表明该方法在实际应用中具有可信度及可行性,为实现类似高效、客观的储层评价提供了新的思路。Abstract: Aiming at the problems of strong subjectivity, complicated calculation procedures and inadequate analysis in traditional reservoir evaluation, the application of the Slack Based Measure model of Data Envelopment Analysis (SBM-DEA model) in comprehensive quantitative evaluation of reservoir was discussed.It is shown that this model has the following advantages:① It could take into account of both the positive and negative related indicators, and is more objective that there is no need to determine the evaluation criterion and index weights by subjective analysis in advance; ②Taking the linear programming as the tool, it could simplify the calculation procedure that it does not have to standardize the evaluation indexes; ③ The evaluation result is between 0-1 naturally, and it can be not only used for sorting and classification of evaluation units, but also providing the reason that units are not efficient as well as the suggestion on how to improve them.The new method was applied in early low-permeability gas reservoir evaluation on the lower section of the eighth member of Shihezi Formation(Middle Permain) in SuX region of Sulige gasfield.Four types of reservoir are classified in the study area and the type Ⅰ and Ⅱ would be the favorable targets.The new evaluation results obtained generally accorded with the traditional fuzzy comprehensive reservoir evaluation results, and showed good consistence with practical field production and geological knowledge.At the same time, the main advice on insufficiency and improvements for this case was given.It is proved that this evaluation method is reliable and practical in application, and provides new thought for similarly effective and objective reservoir evaluation as well.
-
表 1 部分储层评价指标数据及SBM-DEA评价结果
Table 1. Part of reservoir data and evaluation results of SBM-DEA
井号 输出型指标(y) 输入型指标(x) SBM-DEA评价结果 产能/(104m3·d-1) 砂体厚度(y1)/m 孔隙度(y2)/% 渗透率(y3)/10-3 μm2 含气饱和度(y4)/% 泥质质量分数(x1)/% 非均质变异系数(x2) SuX-16-23 21.06 9.50 0.87 57.85 11.25 1.51 1.000 1.768 SuX-17-26 25.88 5.59 0.49 54.63 10.71 2.12 0.727 1.231 SuX-8-11 11.50 6.90 0.57 51.60 12.05 2.10 0.515 1.227 SuX-21-18C1 9.75 6.84 0.38 50.61 12.06 1.79 0.479 1.132 SuX-18-13 14.63 6.44 0.27 47.46 15.26 1.89 0.376 1.116 SuX-16-33 17.03 7.06 0.26 41.44 20.37 1.94 0.347 1.004 SuX-17-17 17.00 6.39 0.26 33.14 13.40 2.22 0.332 0.948 SuX-13-06 18.50 4.94 0.24 39.28 15.89 2.32 0.292 0.725 SuX-11-10 19.60 4.70 0.21 36.77 17.75 2.64 0.230 0.558 SuX-21-22 26.99 5.65 0.20 32.81 16.78 3.41 0.210 0.446 SuX-16-13 11.50 6.65 0.20 35.86 18.36 3.15 0.188 0.329 SuX-15-06 14.35 5.71 0.21 22.32 18.34 3.22 0.176 0.283 SuX-6-09 21.71 4.78 0.16 24.33 20.56 3.22 0.152 0.101 SuX-16-26 23.75 4.35 0.16 14.73 18.38 3.15 0.148 0.094 SuX-19-05 8.87 3.64 0.14 24.10 20.63 3.67 0.112 / SuX-12-19 5.25 3.85 0.13 11.79 18.13 4.64 0.081 / 表 2 苏X-17-26井盒8下段储层单元SBM-DEA评价松弛变量信息
Table 2. SBM-DEA slack variables from the reservoir sample of the lower section of the eighth Member of Shihezi Formation in Well SuX-17-26
评价指标 原始数据 投影结果 松弛变量 砂体厚度(y1)/m 25.88 25.88 s1+=0 孔隙度(y2)/% 5.59 9.35 s2+=3.76 渗透率(y3)/10-3μm2 0.49 0.91 s3+=0.42 含气饱和度(y4)/% 54.63 54.63 s4+=0 泥质质量分数(x1)/% 10.71 10.71 s1-=0 非均质变异系数(x2) 2.12 2.12 s2-=0 -
[1] 裘怿楠, 薛叔浩.油气储层评价技术[M].北京:石油工业出版社, 1997:218-222. [2] 朱兆群, 林承焰, 张苏杰, 等.改进的模糊-灰色综合评判方法在储层定量评价中的应用:以苏里格气田苏X井区盒8下亚段低渗透气藏为例[J].石油与天然气地质, 2017, 38(1):197-208. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT201701022.htm [3] 廖东良, 路保平, 陈延军.页岩气地质甜点评价方法:以四川盆地焦石坝页岩气田为例[J].石油学报, 2019, 40(2):18-25. https://www.cnki.com.cn/Article/CJFDTOTAL-SYXB201902002.htm [4] 张仲宏, 杨正明, 刘先贵, 等.低渗透油藏储层分级评价方法及应用[J].石油学报, 2012, 33(3):437-441. https://www.cnki.com.cn/Article/CJFDTOTAL-SYXB201203013.htm [5] Wang Bei, Liu Xiangjun, Lin Qi, et al.Grading evaluation and prediction of fracture-cavity reservoirs in Cambrian Longwangmiao Formation of Moxi area, Sichuan Basin, SW China[J].Petroleum Exploration and Development, 2019, 46(2):301-313. doi: 10.1016/S1876-3804(19)60010-8 [6] Lu Shuangfang, Li Junqian, Sima Liqiang, et al.Classification of microscopic pore-throats and the grading evaluation on shale oil reservoirs[J].Petroleum Exploration and Development, 2018, 45(3):436-444. http://www.researchgate.net/publication/327780248_Classification_of_microscopic_pore-throats_and_the_grading_evaluation_on_shale_oil_reservoirs [7] Kahneman D, Lovallo D, Sibony O.Before you make that big decision[J].Harvard Business Review, 2011, 89(6):50-60. http://www.tandfonline.com/servlet/linkout?suffix=cit0044&dbid=8&doi=10.1080%2F08878730.2017.1419394&key=21714386 [8] 涂乙, 谢传礼, 刘超, 等.灰色关联分析法在青东凹陷储层评价中的应用[J].天然气地球科学, 2012, 23(2):381-386. https://www.cnki.com.cn/Article/CJFDTOTAL-TDKX201202028.htm [9] 杨正明, 张英芝, 郝明强, 等.低渗透油田储层综合评价方法[J].石油学报, 2006, 27(2):64-67. doi: 10.3321/j.issn:0253-2697.2006.02.013 [10] 陈林, 李珊珊, 游君君, 等.文昌B凹陷古近系低渗储层物性影响因素定量评价与应用[J].地质科技情报, 2019, 38(3):165-173. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201903017.htm [11] Bertolini A C, Schiozer D J.Principal component analysis for reservoir uncertainty reduction[J].Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2016, 38(4):1345-1355. doi: 10.1007/s40430-015-0377-6 [12] Shi Bingbing, Chang Xiangchun, Yin Wei, et al.Quantitative evaluation model for tight sandstone reservoirs based on statistical methods:A case study of the Triassic Chang 8 tight sandstones, Zhenjing area, Ordos Basin, China[J].Journal of Petroleum Science and Engineering, 2019, 173:601-616. doi: 10.1016/j.petrol.2018.10.035 [13] Wang Dongqi, Yin Daiyin, ZhouYazhou.Fine classification of ultra-low permeability reservoirs around the placanticline of Daqing Oilfield (PR of China)[J].Petroleum Exploration and Development, 2018, 45(3):436-444. http://www.sciencedirect.com/science/article/pii/S0920410518310921 [14] Rui Zhenhua, Lu Jun, Zhang Zhien, et al.A quantitative oil and gas reservoir evaluation system for development[J].Journal of Natural Gas Science and Engineering, 2017, 42:31-39. doi: 10.1016/j.jngse.2017.02.026 [15] Zhu Peng, Zhu Zhaoqun, Zhang Yuanyuan, et al.Quantitative evaluation of low-permeability gas reservoirs based on an improved fuzzy-gray method[J].Arabian Journal of Geosciences, 2019, 12(3):80-88. doi: 10.1007/s12517-019-4231-5 [16] 周林, 刘皓天, 周坤, 等.致密砂岩储层"甜点"识别及评价方法[J].地质科技通报, 2020, 39(4):165-173. http://dzkjqb.cug.edu.cn/CN/abstract/abstract10012.shtml [17] 李阳, 代宗仰, 黄蕾, 等.叠合概率法在碳酸盐岩储层评价中的应用:以辽河坳陷西部凹陷高升地区沙四段为例[J].中国石油勘探, 2019, 24(3):361-368. https://www.cnki.com.cn/Article/CJFDTOTAL-KTSY201903009.htm [18] 冯小哲, 祝海华.鄂尔多斯盆地苏里格地区下石盒子组致密砂岩储层微观孔隙结构及分形特征[J].地质科技情报, 2019, 38(3):147-156. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201903015.htm [19] Charnes A, Cooper W W, Rhodes E.Measuring the efficiency of decision making units[J].European Journal of Operational Research, 1978, 2(6):429-444. doi: 10.1016/0377-2217(78)90138-8 [20] 魏权龄.数据包络分析[M].北京:科学出版社, 2004. [21] Huang Chao, Dai Chong, Guo Miao.A hybrid approach using two-level DEA for financial failure prediction and integrated SE-DEA and GCA for indicators selection[J].Applied Mathematics and Computation, 2015, 251:431-441. http://www.sciencedirect.com/science/article/pii/S0096300314016099 [22] Tone K.A slacks-based measure of efficiency in data envelopment analysis[J].European Journal of Operational Research, 2001, 130(3):498-509. http://www.researchgate.net/publication/4869350_Tone_K_A_slacks-based_measure_of_efficiency_in_data_envelopment_analysis_Eur_J_Oper_Res_130_498-509 [23] Cecchini L, Venanzi S, Pierri A, et al.Environmental efficiency analysis and estimation of CO2 abatement costs in dairy cattle farms in Umbria (Italy):A SBM-DEA model with undesirable output[J].Journal of Cleaner Production, 2018, 197:895-907. http://www.sciencedirect.com/science/article/pii/S0959652618318158 [24] 杨少春, 温雅茹, 李媛媛, 等.利用数据包络分析法表征碎屑岩储层非均质性[J].中南大学学报:自然科学版, 2016, 47(1):218-224. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNGD201601030.htm [25] 马宝全, 杨少春, 张鸿, 等.基于DEA定量表征低渗透砂岩储层成岩相:以鄂尔多斯盆地演武地区延长组8~1段为例[J].中国矿业大学学报, 2018, 47(2):357-366. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGKD201802016.htm [26] 马占新, 任慧龙, 戴仰山.基于模糊综合评判方法的DEA模型[J].模糊系统与数学, 2001(3):61-67. https://www.cnki.com.cn/Article/CJFDTOTAL-MUTE200103015.htm [27] 吴文江, 刘亚俊.DEA中确定指标是输入(出)的根据及其应用[J].运筹与管理, 2000(4):67-70. https://www.cnki.com.cn/Article/CJFDTOTAL-YCGL200004012.htm [28] Daraei M, Bayet-Goll A, Ansari M.An integrated reservoir zonation in sequence stratigraphic framework:A case from the Dezful Embayment, Zagros, Iran[J].Journal of Petroleum Science and Engineering, 2019, 154:389-404. http://www.sciencedirect.com/science/article/pii/S0920410516311512